Senior Data Scientist, Pricing Algorithms

December 19

🇺🇸 United States – Remote

🤠 Texas – Remote

Although this job is listed in Texas, this company may be open to hiring remote in other states.

⚔️ Virginia – Remote

Although this job is listed in Virginia, this company may be open to hiring remote in other states.

⏰ Full Time

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

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CarMax

WebsiteLinkedInAll Job Openings

Retail and Used Cars

10,000+ employees

Founded 1993

🛒 Retail

💰 Post-IPO Equity on 2021-06

Description

• Develop new models and improve our existing models • Interpret, validate, and apply feature engineering to large and complex pricing-related data sets • Find creative ways to incorporate new insights and data sources • Leverage statistical / machine learning techniques and sound reasoning to develop, validate, and improve predictive models • Design controlled experiments to assess the business value of new models • Present insights and recommendations to senior leaders to drive change • Help CarMax continue to develop its data expertise • Research innovations and best practices related to data sources, modeling methodologies, and data science tools • Influence the team in the development of our modeling capability strategic roadmap • Effectively communicate how our models work to team members, both at a general level and a detailed level

Requirements

• Target mindset: Curious, skeptical, creative, committed to learning and staying informed on the latest techniques in data science, with a strong attention to detail and commitment to sound reasoning • Required experience: Either a bachelor’s degree in a quantitative discipline OR equivalent experience and training through past employment • At least 2 years relevant work experience (Advanced study in a quantitative field may substitute for work experience), including experience applying strong foundational math and/or modeling skills to solve complex problems • Ideal candidates would have experience with these behaviors: Extracting and sharing clear insights from modelling • Project management, ideally including end-to-end experience with the machine learning deployment pipeline • Relationship building and collaboration • Preferred skills, certifications, or knowledge areas: Expertise in selecting and applying various modeling techniques (supervised & unsupervised, classification & regression, etc.), Python/SQL programming • Data cleaning and pre-processing • Statistical and probabilistic analysis